The brain criticality hypothesis has largely only characterized brain dynamics in terms of their self-similarity, although experimental evidence suggests that the brain exhibits significant multifractality. To understand how multifractality may emerge in critical-like systems modeling neuronal activity, we used a neural field model exhibiting neural oscillations and a critical phase transition. We find that multifractality emerges near a synchronization phase transition, and that the pattern of variation in multifractality changes when placing the model at a different phase transition. These findings show that multifractality in temporal dynamics emerges near criticality in neural fields, providing a formal basis for interpreting multifractality in brain recordings.

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• Dynamic critical phenomena
• First order phase transitions
• Neuronal dynamics
• Scaling laws of complex systems
• Nonequilibrium lattice models
• Fractal analysis
• Time series analysis